Autonomous Controller Design for Unmanned Aerial Vehicles using Multi-objective Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{oh:2004:acdfuavumgp,

• title = "Autonomous Controller Design for Unmanned Aerial Vehicles using Multi-objective Genetic Programming",
• author = "Choong K. Oh and Gregory J. Barlow",
• pages = "1538--1545",
• booktitle = "Proceedings of the 2004 IEEE Congress on Evolutionary Computation",
• year = "2004",
• publisher = "IEEE Press",
• month = "20-23 " # jun,
• address = "Portland, Oregon",
• ISBN = "0-7803-8515-2",
• keywords = "genetic algorithms, genetic programming, Real-world applications, Multiobjective evolutionary algorithms, multi-objective optimisation, unmanned aerial vehicles, evolutionary robotics",
• URL = "http://www.cs.cmu.edu/~gjb/includes/publications/conference/oh2004-cec/oh2004-cec.pdf",
• DOI = "doi:10.1109/CEC.2004.1331079",
• abstract = "Autonomous navigation controlers were developed for fixed wing unmanned aerial vehicle (UAV) applications using multi-objective genetic programming (GP). We designed four fitness functions derived from flight simulations and used multi-objective GP to evolve controllers able to locate a radar source, navigate the UAV to the source efficiently using on-board sensor measurements, and circle closely around the emitter. Controllers were evolved for three different kinds of radars: stationary, continuously emitting radars, stationary, intermittently emitting radars, and mobile, continuously emitting radars. We selected realistic flight parameters and sensor inputs to aid in the transference of evolved controllers to physical UAVs.",
• notes = "CEC 2004 - A joint meeting of the IEEE, the EPS, and the IEE.",

}

Genetic Programming entries for Choong K Oh Gregory J Barlow

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